The introduction of large language models (LLMs) has revolutionized the field of artificial intelligence, providing organizations with the tools to innovate and stay ahead in the competitive landscape. However, the regional availability of these LLMs has posed a challenge for many enterprises, forcing them to wait until models are accessible in their tech stack’s location. This delay can hinder progress and put companies at a disadvantage in the fast-paced world of AI development.
To address the issue of regional availability and accelerate AI development, Snowflake recently announced the general availability of cross-region inference. This new feature allows developers to process requests on Cortex AI in a different region, even if a specific model is not yet available in their source region. By enabling cross-region inference, organizations can seamlessly integrate new LLMs as soon as they become available, regardless of their geographical location.
Enabling cross-region inference requires developers to set parameters that specify regions for inference processing. If both regions operate on the same cloud provider, such as Amazon Web Services (AWS), data can securely traverse the global network with automatic encryption at the physical layer. However, if regions are on different cloud providers, traffic will cross the public internet via encrypted transport. It is important to note that inputs, outputs, and prompts are not stored or cached during inference processing, ensuring data privacy and security.
In order to execute inference and generate responses within the Snowflake perimeter, users must configure account-level parameters to determine where inference will take place. Cortex AI will automatically select a region for processing if the requested LLM is not available in the source region. For example, by setting a parameter to “AWS_US,” the inference can be processed in either the U.S. east or west regions. Currently, target regions are limited to AWS, so requests will default to processing in AWS if cross-region inference is enabled in Azure or Google Cloud.
The implementation of cross-region inference offers numerous benefits for organizations looking to leverage LLMs for AI development. By allowing seamless integration of models regardless of regional availability, companies can expedite the innovation process and stay ahead of the competition. This feature simplifies the deployment of new LLMs and ensures that organizations can make the most of these advanced AI technologies without incurring additional egress charges.
The introduction of cross-region inference by Snowflake marks a significant milestone in the advancement of AI development. By overcoming the critical obstacle of regional availability, organizations can now harness the power of large language models without being limited by geographical constraints. This new feature paves the way for accelerated innovation and growth in the field of artificial intelligence, providing companies with the tools they need to succeed in today’s competitive market.
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